Analysis of Technical Requirements for Semi-Finished Rolled Products for Coiled Tubing
Bibliographic record
Abstract
In the course of time, the need for such resources as oil, gas and gas condensate is constantly growing, leading to an increase in the depth of wells, the use of more complex structures (transition from vertical shafts to inclined and horizontal ones with a length of over 2000 m), as well as an increase in a share of mining from hard-to-recover reserves.One of the most promising methods for exploiting, developing and maintaining a well is a method based on the use of a string of flexible flush-joint steel tubes, also known as the coiled tubing technology.In order to assess the state of production of steel products for coiled tubing, the authors analyzed the technical requirements of Russian and foreign manufacturers.A guarantee of a trouble-free operation of coiled tubing in severe operating conditions is the use of structural high-strength low-alloy steel with high strength and impact toughness, high flex life, as well as increased resistance to atmospheric corrosion.The main foreign manufacturers of coiled tubing are the USA, Canada and China.In Russia coiled tubing is produced by ESTM plant (the city of Uzlovaya).Russian and foreign manufacturers set similar requirements for a level of mechanical properties of semi-finished rolled products for coiled tubing, which can be achieved by using a scheduled chemical composition and special parameters of thermomechanical processing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".